Imaging the Ionospheric Electron Density Using a Combined Tomographic Algorithm

Debao Wen

Abstract:	A new algorithm, which is the combination of the generalized singular value decomposition (GSVD) and the improved algebraic reconstruction technique (IART), is proposed to image ionospheric electron density 쳌iIED쳌j distribution in this paper. In this new method, the GSVD is first used to resolve the ill-posed problem in computerized ionospheric tomography (CIT) system. Its estimate inverted from total electron content (TEC) measurements is then provided as the initial approximation required by the IART. The combined algorithm therefore offers a more reasonable approach to choose an initial approximation for the IART and improve the quality of the final reconstructed image. A numerical simulation experiment demonstrates that the combined algorithm is more accurate than the GSVD alone or the IART alone for the tomographic inversion of IED. The new method is then applied to perform the inversion of the IED during a magnetically disturbed period on 21 August 2003. Tomographic results show that the main ionospheric effects of this storm over China are as follows: the negative storm phase effect appears in F region, the positive storm phase effect occurs above F region, and meanwhile, some prominent features in the ionospheric structure can be revealed in the ionospheric images, such as the disturbance and mid-latitude trough. The reliability of the new method is also validated by the ionosonde data recorded at Wuhan station.
Published in:	Proceedings of the 20th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2007) September 25 - 28, 2007 Fort Worth Convention Center Fort Worth, TX
Pages:	2337 - 2345
Cite this article:	Wen, Debao, "Imaging the Ionospheric Electron Density Using a Combined Tomographic Algorithm," Proceedings of the 20th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2007), Fort Worth, TX, September 2007, pp. 2337-2345.
Full Paper:	ION Members/Non-Members: 1 Download Credit Sign In